Biography
Jola is a Senior Computational Scientist working at the overlap of Scientific Machine Learning (SciML) and CCP-EM research groups. Her research focuses on applying machine learning and computer vision solutions to improve understanding of multi-dimensional and visual data in structural biology, in particular within electron cryo-microscopy (cryo-EM). Jola completed her undergraduate degree in AI and Robotics at Aberystwyth University and obtained her doctoral degree from the University of Oxford. Her DPhil thesis focused on using machine learning to understand the functional basis of cancerous tumours during their longitudinal development. In her spare time, she enjoys rock climbing and alpinism.
(CCP-EM link https://www.ccpem.ac.uk/)
Peer-reviewed publications:
- J. Mirecka et al. “Variation-guided supervoxels for subregional tumour analysis in DCE-MRI”, ISMRM 2018
H. Winter*, J. Mirecka* et al. “Clinical feasibility of texture analysis in DCE-MRI of patients receiving selective internal radiation therapy”, NCRI 2017 and European Journal of Surgical Oncology - abstract (*joint)
B. Irving, J. Mirecka, et al. “Perfusion-supervoxels for DCE-MRI based tumour subregion assessment”, ISMRM 2017
J. Mirecka et al. “Statistical texture modelling of tumour perfusion heterogeneity in DCE-MRI”, CMMI (MICCAI) 2015
J. Mirecka et al. “Random projections for mammographic texture segmentation and high/low risk classification”, BIA (MICCAI) 2015
